1. Field of the Invention
The present invention relates to an image enhancement method. More particularly, it relates to an image enhancement method using a histogram equalization.
This application for an image enhancement method using histogram equalization is based on Korean Patent Application no. 96-24412 which is incorporated herein by reference for all purposes.
2. Description of the Related Arts
In general, the distribution of gray levels in a given input image is referred to as a histogram. The histogram of gray levels provides an overall description of the appearance of the input image. Proper adjustment of gray levels for a given image can enhance the appearance or contrast of the image.
Among the many methods for contrast enhancement, the most widely known one is the histogram equalization, in which the contrast of a given image is enhanced according to the sample distribution thereof. The method is disclosed in documents: 1! J. S. Lim, "Two-dimensional Signal and Image Processing," Prentice Hall, Englewood Cliffs, N.J., 1990, and 2! R. C. Gonzalez and P. Wints, "Digital Image Processing," Addison-Wesley, Reading, Mass., 1977.
Also, the useful applications of the histogram equalization method for medical image processing and radar image processing are disclosed in documents: 3! J. Zimmerman, S. Pizer, E. Staab, E. Perry, W. McCartney and B. Brenton, "Evaluation of the Effectiveness of Adaptive Histogram Equalization for Contrast Enhancement," IEEE Transaction on Medical Imaging, pp. 304-312, December. 1988, and 4! Y. Li, W. Wang and D. Y. Yu, "Application of Adaptive Histogram Equalization to X-ray Chest Image," Proc. of the SPIE, pp. 513-514, vol. 2321, 1994.
In general, since histogram equalization causes the dynamic range of an image to be stretched, the density distribution of the resultant image is made more flat and the contrast of the image is enhanced as a consequence.
However, such a widely-known feature of the histogram equalization becomes a defect in some practical cases. In particular, the mean brightness of the image may change significantly as a result of the equalization. Furthermore, noise in the image is equalized along with the image signal. This may cause the noise to be greatly amplified, which deteriorates the quality of the image. Such problems typically occur when the input samples in the image are concentrated in a few gray levels.